60 citations · 140 across the 9 of their papers we have counts for
4 papers · 1 filter
Controlling Model Complexity in Probabilistic Model-Based Dynamic Optimization of Neural Network Structures
Shota Saito, Shinichi Shirakawa
A method of simultaneously optimizing both the structure of neural networks and the connection weights in a single training loop can reduce the enormous computational cost of neura…
Sample Reuse via Importance Sampling in Information Geometric Optimization
Shinichi Shirakawa, Youhei Akimoto, Kazuki Ouchi +1
In this paper we propose a technique to reduce the number of function evaluations, which is often the bottleneck of the black-box optimization, in the information geometric optimiz…
Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling
Shinichi Shirakawa, Yasushi Iwata, Youhei Akimoto
Deep neural networks (DNNs) are powerful machine learning models and have succeeded in various artificial intelligence tasks. Although various architectures and modules for the DNN…
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures
Masanori Suganuma, Shinichi Shirakawa, Tomoharu Nagao
The convolutional neural network (CNN), which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures…